Windpassinger, S. | bioRxiv Science

bioRxiv2026

NOHIC: A PIPELINE FOR PLANT CONTIG SCAFFOLDING USING PERSONALIZED REFERENCES FROM PANGENOME GRAPHS

Hi-C data is commonly used for reference-free de novo scaffolding. However, with the rapid increase in high-quality reference genomes, reference-guided workflows are now more practical for assembling large numbers of target genomes without relying on costly and labor-intensive Hi-C sequencing. Recently, a pangenome graph-based haplotype sampling algorithm was introduced to generate personalized graphs for target genomes. Such graphs have strong potential as references for reference-guided contig scaffolding. Here, we present noHiC, a reference-guided scaffolding pipeline supporting key steps of plant contig scaffolding. A distinctive feature of noHiC is the nohic-refpick script, generating a best-fit synthetic reference (synref) from a pangenome graph that is genetically close to the target contigs. This enables the integration of genetic information from many references (up to 48 in our tests) without using them separately during scaffolding. Synrefs showed advantages over highly contiguous conventional references in reducing false contig breaking during reference-based correction. Additionally, nohic-refpick can be combined with fast scaffolders (ntJoin) to rapidly produce highly contiguous assemblies using synrefs derived from pangenome graphs. The noHiC pipeline, used alone or in combination with ntJoin, can generally produce assemblies that are structurally consistent with public Hi-C-based or manually curated genomes. The pipeline is publicly available at https://github.com/andyngh/noHiC. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/712436v1_ufig1.gif" ALT="Figure 1"> View larger version (9K): org.highwire.dtl.DTLVardef@40bd8forg.highwire.dtl.DTLVardef@5d2bbborg.highwire.dtl.DTLVardef@e214a3org.highwire.dtl.DTLVardef@b90b06_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2022

Genetic diversity analysis and characterization of Ugandan sorghum

The National Genebank of Uganda houses diverse and rich Sorghum bicolor germplasm collection. This genetic diversity resource is untapped, under-utilized and has not been systematically incorporated into sorghum breeding programs. In this study, we characterized the germplasm collection using whole genome SNP markers. Discriminant analysis of principal components (DAPC) was implemented to study racial ancestry of the accessions in comparison to a global sorghum diversity set and characterize sub-groups and admixture in the Ugandan germplasm. Genetic structure and phylogenetic analysis was conducted to identify distinct genotypes in the Ugandan collection and relationships among groups. Furthermore, in a case study for identification of potentially useful adaptive trait variation for breeding, we performed genome-wide association studies for juvenile cold tolerance. Genomic regions potentially involved in adaptation of Ugandan sorghum varieties to cooler climatic conditions were identified that could be of interest for expansion of sorghum production into temperate latitudes. The study demonstrates how genebank genomics can potentially facilitate effective and efficient usage of valuable, untapped germplasm collections for agronomic trait evaluation and subsequent allele mining.

plant biology↗